Rapid sampling of Escherichia coli after changing oxygen conditions reveals transcriptional dynamics

Escherichia coli is able to shift between anaerobic and aerobic metabolism by adapting its gene expression, e.g., of metabolic genes, to the new environment. The dynamics of gene expression that result from environmental shifts are limited, amongst others, by the time needed for regulation and transcription elongation. In this study, we examined gene expression dynamics after an anaerobic-to-aerobic shift on a short time scale (0.5, 1, 2, 5, and 10 min) by RNA sequencing with emphasis on delay times and transcriptional elongation rates (TER). Transient expression patterns and timing of differential expression, characterized by delay and elongation, were identified as key features of the dataset. Gene ontology enrichment analysis revealed early upregulation of respiratory and iron-related gene sets. We inferred specific TERs of 89 operons with a mean TER of 42.0 nt/s and mean delay time of 22.4 s. TERs correlate with sequence features, such as codon bias, whereas delay times correlate with the involvement of regulators. The presented data illustrate that at very short times after a shift in oxygenation, extensional changes of the transcriptome, such as temporary responses, can be observed. Besides regulation, TERs contribute to the dynamics of gene expression

Model-based analysis of an adaptive evolution experiment with Escherichia coli in a pyruvate limited continuous culture with glycerol

Bacterial strains that were genetically blocked in important metabolic pathways and grown under selective conditions underwent a process of adaptive evolution: certain pathways may have been deregulated and therefore allowed for the circumvention of the given block. A block of endogenous pyruvate synthesis from glycerol was realized by a knockout of pyruvate kinase and phosphoenolpyruvate carboxylase in E. coli. The resulting mutant strain was able to grow on a medium containing glycerol and lactate, which served as an exogenous pyruvate source. Heterologous expression of a pyruvate carboxylase gene from Corynebacterium glutamicum was used for anaplerosis of the TCA cycle. Selective conditions were controlled in a continuous culture with limited lactate feed and an excess of glycerol feed. After 200–300 generations pyruvate-prototrophic mutants were isolated. The genomic analysis of an evolved strain revealed that the genotypic basis for the regained pyruvate-prototrophy was not obvious. A constraint-based model of the metabolism was employed to compute all possible detours around the given metabolic block by solving a hierarchy of linear programming problems. The regulatory network was expected to be responsible for the adaptation process. Hence, a Boolean model of the transcription factor network was connected to the metabolic model. Our model analysis only showed a marginal impact of transcriptional control on the biomass yield on substrate which is a key variable in the selection process. In our experiment, microarray analysis confirmed that transcriptional control probably played a minor role in the deregulation of the alternative pathways for the circumvention of the block

Transition of an Anaerobic Escherichia coli Culture to Aerobiosis: Balancing mRNA and Protein Levels in a Demand-Directed Dynamic Flux Balance Analysis.

The facultative anaerobic bacterium Escherichia coli is frequently forced to adapt to changing environmental conditions. One important determinant for metabolism is the availability of oxygen allowing a more efficient metabolism. Especially in large scale bioreactors, the distribution of oxygen is inhomogeneous and individual cells encounter frequent changes. This might contribute to observed yield losses during process upscaling. Short-term gene expression data exist of an anaerobic E. coli batch culture shifting to aerobic conditions. The data reveal temporary upregulation of genes that are less efficient in terms of energy conservation than the genes predicted by conventional flux balance analyses. In this study, we provide evidence for a positive correlation between metabolic fluxes and gene expression. We then hypothesize that the more efficient enzymes are limited by their low expression, restricting flux through their reactions. We define a demand that triggers expression of the demanded enzymes that we explicitly include in our model. With these features we propose a method, demand-directed dynamic flux balance analysis, dddFBA, bringing together elements of several previously published methods. The introduction of additional flux constraints proportional to gene expression provoke a temporary demand for less efficient enzymes, which is in agreement with the transient upregulation of these genes observed in the data. In the proposed approach, the applied objective function of growth rate maximization together with the introduced constraints triggers expression of metabolically less efficient genes. This finding is one possible explanation for the yield losses observed in large scale bacterial cultivations where steady oxygen supply cannot be warranted

Einführung in das chilenische Theater

Einführung in das chilenische Theater. - In: Das moderne Theater Lateinamerikas / Wilfried Floeck ... (Hrsg.). - Frankfurt am Main : Vervuert, 1993. - S. 91-96. - (Americana Eystettensia : A, Kongreßakten ; 11

Correlation of transcriptional fold changes with FBA flux rate differences.

<p>The difference between the sums of absolute FBA fluxes with identical enzyme composition between anaerobic and aerobic conditions is plotted against the logFC of the associated transcripts. Spearman rank coefficient and P-values are indicated. Linear regression is shown as black line with 95% confidence bands in red.</p

Alternative pathways for reoxidation of NADH.

<p>Alternative pathways for reoxidation of NADH.</p

Outline of central aerobic metabolism.

<p>Reaction nomenclature according to iJO1366 [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158711#pone.0158711.ref014" target="_blank">14</a>]. Pyr, pyruvate; ICit, Isocitric acid; <i>α</i>-KG, <i>α</i>-ketoglutaric acid; Suc-CoA, succinyl-coenzyme A; Succ, succinic acid; Mal, malic acid; OxAc, oxaloacetic acid; UQ, ubiquinone; UQH₂, ubiquinol; only redox cofactors are considered.</p

Parameters for dddFBA modeling.

<p>Parameters for dddFBA modeling.</p

Fluxes of balanced genes in dddFBA.

<p>Fluxes are depicted as green lines, upper flux bounds as dashed light green lines, flux variability as shadowed areas and correspond to the left axis; measured mRNA expression as blue dots with standard deviations, and simulated mRNA expression in light blue correspond to the right axis. 0 min denote the onset of aeration.</p